Predicting Customer Behaviour Using a Self-Organizing Map and Comparing with Random Forest

The main of this paper is to analyse the performance of customer behaviour in online shopping by using precision value.A novel Self-organizing map with Random Forest was iterated at different times for predicting accuracy percentage of customer behaviour. The result proved that the Novel Self-organizing map got significant results with 96% accuracy compared to Random Forest with 93% accuracy. Self-organizing mapis a simple and most effective algorithm to build fast machine learning models. The self-organizing map helps in predicting with more accuracy the percentage of customer behaviour.